With the continuing development of globally interconnected communication networks, a need has arisen for robust interconnection amongst communication networks servicing respective regions and entities. In traditional network operation practices, network level modeling can become very complex due to the number of paths that have to be calculated and installed on the network to be able to deploy multiple service types in terms of routes.
Providing multiple redundant, bandwidth efficient paths over a data network ensuring traffic handling behavior is predictable is a challenge for network operators. Usually the solution is throwing more bandwidth at the problem, but this has its inherent drawbacks and sometimes it is actually not possible to increase bandwidth capacity right away for a number of reasons. Building, operating and maintaining a backbone network requires a large amount of money and time invested not only in hardware and software but in planning and deploying its components, then it is imperative to efficiently manage the network resources to ensure the investment is effectively returned within the expected time-frame and margin. On the other hand squeezing too much the networks resources could lead to improper traffic handling, data loss, instability and ultimately impacting negatively the service level and customer experience.
A way to effectively manage both capacity and traffic is needed, or else it would not be possible to provide a highest quality service at a fair price. To meet that goal, it is needed not only to centralize network intelligence separating the control plane from the data plane but bringing the business plane into the equation.
As an example, a Path Count Calculation for a given partially-meshed Network, designed in terms of link count and topology to accommodate an Average Number of 3 Paths per Service Type, with 4 Service Types over a Network with 25 nodes, results in 7200 possible Paths.